1. Field of the Invention
The invention relates to the separation of foreground information from background information in a document.
2. Description of the Art
In order to be able to carry out an image or character recognition procedure (optical character recognition) in an electronically-scanned and digitalized document, it is frequently necessary, in an initial preparatory stage (image preprocessing) for foreground information to be separated from the background information. In this situation, the foreground information is often the actual image information which comes into consideration for the character recognition, while the background information in many cases has an interfering effect, and may even lead to misinterpretation of the foreground information. The background information of the picture also frequently contributes to a reduction in the identification performance of the foreground information. The background information should therefore, for preference, be removed before the picture or character recognition. Foreground information, which is intended to represent a script, is, in many applications, required to be converted by the subsequent character recognition, for preference into ASCII data.
The background data in a picture is in most cases composed of the following groups: interference in digitalization (such as noise), and components of the digitalized document which cannot be filtered out (such as dirt, script fragments, stamps, etc.). In order to achieve the best possible identification rate in a subsequent processing stage, the image data should, for preference, after an image processing procedure, only contain that data which it is intended should be processed later by the character recognition process. The better the image processing prior to recognition, the more favorable the recognition results can be expected to be.
Many image processing units expect, as input, an image reduced in the grey scales; e.g. a binarised black/white image. For the production of an electronically-scanned image of document, reader devices (scanners) are frequently used, which supply images at a predetermined scanning frequency (e.g. 200 to 300 pixels per square inch), with a large number of grey scales (e.g. 16 or 256 grey scales).
Due to a series of potential faults when a document is being read in, such as, for example, scanner tolerances or an inadequate match or balance between the individual laser elements of a scanner, it is possible that a series of influencing factors may arise as early as at this stage, which could exert a disadvantageous effect on image recognition. Likewise, the type and quality of the document itself may decisively influence the image recognition. For example, color contrasts which may be present might be lost during the conversion of a color image into a grey image. In the case of handwritten entries on a document, but with typewritten entries too, the readability and recognition capacity also depend in particular on the degree of contrast involved, caused for example by a more or less strong pressure exerted when writing, etc.
For a series of applications, there is a requirement for what is known as an archive picture to be created in addition to the character recognition, in order, for example, to reduce the amount of paper used. In other words, two images have to be created, which should, as far as possible, be done without loss of throughput. Of the applications available at the moment, black/white pictures are used for this purpose, both for the recognition unit as well as for archiving purposes. Grey scale images must be intensively compressed and decompressed by computer processing, which accordingly means they have a higher memory requirement than black/white pictures.
By electronic scanning of a document, an electronic image of the document is obtained, in which an image value is allocated to every pixel, for example a grey value, a black or white value, or a color value. By means of the use of filters, these allocations can be influenced. With the use of a threshold value filter, for example, the picture values above or below a predetermined threshold value can be filtered out of the electronic image. Thus, for example, the background information which is not desired for an image processing procedure, or interference effects, can be eliminated.
The image values which are filtered out, however, will no longer be available thereafter for image recognition. Foreground information which may be inadvertently filtered out might therefore falsify the result of subsequent image recognition. Depending on the value of the threshold value, more or less information will be lost. The choice of the threshold value therefore acquires paramount significance for the quality of image recognition.
To generate binary images from grey scale images, static or dynamic conversion algorithms are frequently used. To achieve a less contaminated background, color filters are frequently used, or the document is illuminated with the appropriate colored light. Traditional filter operations (such as morphological) are used to eliminate selected structures (such as straight horizontal or vertical lines), and are tailored to specific events in a specific environment (document type).
According to the book by Peter Habercker, "Digital Image Processing", Carl Hanser Verlag, Munich and Vienna, ISBN 3-44614442-0, 1985, a series of procedures for image processing are known, which can also be applied to an image preprocessing procedure. In particular, this describes operations in the locational vicinity (Section 8), processes for smoothing the grey values (Section 8.1), and the use of difference operators (Section 8.2), as well as procedures for dynamic threshold value determination (Section 12.3).
An overview of the best-known processes for determining a threshold value is provided in P. K. Sahoo, S. Soltani, and A. K. C. Wong, "A Survey of Thresholding Techniques", Computer Vision, Graphics and Image Processing 41, 233-260, 1988. A distinction is drawn in this work between histogram transformation methods, which change the form of a histogram of a grey value allocation in order to determine the threshold value, and algorithms for threshold value calculation.
From U.S. Pat. No. 4,590,606 and U.S. Pat. No. 5,038,381, further procedures are known for image processing, such as foreground filters by means of transit-time behavior.
EP-A-0.505.729 describes a system for binarisation of images, which will make possible the reading of documents with a normal print quality.
One thing which is, however, common to all processes with filtering-out of information from an electronic document is that the filtering process may cause the loss of information which is necessary for image recognition.